Assessing the logistics efficiency of European countries by using the DEA-PC methodology

Data envelopment analysis is a non-parametric linear programming method widely used for the efficiency evaluation of decision making units active in the transport sector. However, it is seldom applied for the efficiency assessment of logistics efficiency at a macro level. The article presents such an example which is at the same time the very first application of a lately developed methodology where data envelopment analysis is combined with analytic hierarchy process to yield an appropriate tool for efficiency evaluation with full ranking. The logistics efficiency of 29 European countries is tested with the new DEA-PC (pairwise comparison) methodology while it is also compared with the results gained with the original DEA method. Furthermore, the outcomes are also evaluated in light of the ‘Logistics quality and competence’ index of the Logistics Performance Indicator (LPI), a major international survey into the logistics competence of countries. Thus, the results of traditional DEA and DEA-PC are both weighted against survey data which is also a novelty in the logistics sector.

[1]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[2]  Jian Cai,et al.  Improving supply chain performance management: A systematic approach to analyzing iterative KPI accomplishment , 2009, Decis. Support Syst..

[3]  Rajat Bhagwat,et al.  Performance measurement of supply chain management: A balanced scorecard approach , 2007, Comput. Ind. Eng..

[4]  Peihua Fu,et al.  Evaluating Efficiency and Effectiveness of Logistics Infrastructure Based on PCA-DEA Approach in China , 2009, 2009 Second International Conference on Intelligent Computation Technology and Automation.

[5]  Maria Jose Verdecho,et al.  An information architecture for a performance management framework by collaborating SMEs , 2010, Comput. Ind..

[6]  Zilla Sinuany-Stern,et al.  Review of ranking methods in the data envelopment analysis context , 2002, Eur. J. Oper. Res..

[7]  Kevin Cullinane,et al.  The technical efficiency of container ports: Comparing data envelopment analysis and stochastic frontier analysis , 2006 .

[8]  Patricia J. Daugherty,et al.  Investigating the influence of velocity performance on satisfaction with third party logistics service , 2010 .

[9]  Rita Markovits-Somogyi,et al.  Measuring Efficiency in Transport: The State of the Art of Applying Data Envelopment Analysis , 2011 .

[10]  Tomas Baležentis,et al.  ASSESSING THE EFFICIENCY OF LITHUANIAN TRANSPORT SECTOR BY APPLYING THE METHODS OF MULTIMOORA AND DATA ENVELOPMENT ANALYSIS , 2011 .

[11]  Ying Luo,et al.  Common weights for fully ranking decision making units by regression analysis , 2011, Expert Syst. Appl..

[12]  János Fülöp,et al.  Ranking decision making units based on DEA-like nonreciprocal pairwise comparisons , 2012 .

[13]  Margarita Išoraite,et al.  Evaluating efficiency and effectiveness in transport organizations , 2005 .

[14]  Rodney H. Green,et al.  Efficiency and Cross-efficiency in DEA: Derivations, Meanings and Uses , 1994 .

[15]  William W. Cooper,et al.  MODELS AND MEASURES FOR EFFICIENCY DOMINANCE IN DEA Part I: Additive Models and MED Measures * , 1996 .

[16]  A. U.S.,et al.  Measuring the efficiency of decision making units , 2003 .

[17]  Lauri Ojala,et al.  Connecting to Compete 2010 , 2010 .

[18]  Stanley E. Fawcett,et al.  Logistics Performance Measurement and Customer Success , 1998 .

[19]  Gábor Kovács,et al.  Applying a multi-criteria decision methodology in the implementation of tenders for the acquisition of the infrastructure of logistics systems , 2009 .

[20]  Changbing Jiang,et al.  Research on Logistics Network Infrastructure Based on HCA and DEA-PCA Approach , 2010, J. Comput..

[21]  K. Platts,et al.  Supplier logistics performance measurement: Indications from a study in the automotive industry , 2004 .

[22]  P. Andersen,et al.  A procedure for ranking efficient units in data envelopment analysis , 1993 .

[23]  M. Wen,et al.  Fuzzy data envelopment analysis (DEA): Model and ranking method , 2009 .

[24]  T. Sexton,et al.  Data Envelopment Analysis: Critique and Extensions , 1986 .

[25]  Zilla Sinuany-Stern,et al.  An AHP/DEA methodology for ranking decision making units , 2000 .

[26]  Daniel J. Graham,et al.  Productivity and efficiency in urban railways: Parametric and non-parametric estimates , 2008 .

[27]  T.C.E. Cheng,et al.  An empirical study of supply chain performance in transport logistics , 2004 .